Wireless networking connects one or more wireless devices to other computer devices without a direct electrical connection, such as a copper wire or optical cable. Wireless devices communicate data, typically in the form of packets, across a wireless or partially wireless computer network and open a “data” or “communication” channel on the network such that the device can send and receive data packets. The wireless devices often have wireless device resources, such as programs and hardware components, which individually and cooperatively operate to use and generate data in accordance to their design and specific protocol or configuration, such as using open communication connections to transmit and receive data on the network.
Wireless devices are being manufactured with increased computing capabilities and are becoming tantamount to personal computers and include such features as Internet browsing, instant messaging (“IM”), E-mail, and text messaging, including Short Message Service and Multimedia Messaging Service (“SMS/MMS”). Because such features facilitate direct contact with a wireless device user, these messaging clients have become targets for unauthorized, unsolicited, and in most cases unwanted, messages and/or viruses, herein referred to as “spam.”
Spamming may be loosely defined as the use of any electronic communications medium to send unsolicited messages and/or viruses in bulk and by definition, occurs without the permission of the recipient. While its use is usually limited to indiscriminate bulk mailing and not any targeted marketing, the term “spam” can refer to any commercially oriented, unsolicited bulk mailing perceived as being excessive and undesired. Although the most common form of spam is that delivered in E-mail, spammers have developed a variety of spamming techniques, which vary by media: E-mail spam, instant messaging spam, Usenet newsgroup spam, Web search engines spam, weblogs spam, and mobile phone messaging spam.
Spam by E-mail is a type of spam that involves sending identical (or nearly identical) messages to thousands (or millions) of recipients. Spammers often harvest addresses of prospective recipients from Usenet postings and/or web pages, obtain them from databases, or simply guess them by using common names and domains.
Instant messaging (“IM”) systems, such as Yahoo! Messenger, AIM, MSN Messenger and ICQ, are popular targets for spammers. Many IM systems offer a directory of users, including demographic information such as age and sex. Advertisers can gather this information, sign on to the system, and send unsolicited messages.
Mobile phone spam, in some forms, includes spamming directed at mobile phone text messaging services and can be especially irritating to users not only for the inconvenience but also because they may have to pay to receive the unsolicited and often unwanted text message. Mobile phone spam may also include any type of content that can be received by a mobile phone, such as audio content, video content, software programs, etc., and combinations thereof.
Several methods of message analysis to protect networks from spam include fingerprinting and rules-based scoring. Fingerprinting technology takes a “digital picture” of each message and matches it against known profiles of spam messages to detect unwanted email and flag it as spam. Rule-based scoring involves scoring messages against a database of spam rules, assigning scores to messages based on unique characteristics of spam and legitimate email. When a score of a message exceeds a defined threshold, it is flagged as spam.
The approach to anti-spam filtering at the wireless user device level, has for the most part, been accomplished by incorporating an anti-spam module within each messaging client application. However, if anti-spam code is integrated within each client application, e.g., E-mail, MMS, SMS, and IM, much valuable handset storage/memory is wasted doing essentially the same function, that being anti-spam filtering.
Furthermore, if the functionality of an anti-spam module is limited to filtering spam after being received by the wireless device, the filtering does nothing to address the equally if not more important issue of network congestion due to a flood of spam traversing the network. A network, accurately sized for a certain bandwidth of legitimate traffic (plus a little extra) may be hard pressed to maintain the designed-to quality-of-service in the presence of millions of instances spam content directed to an equally large and growing number of wireless devices hosting several content consuming client applications.
Accordingly, it would be advantageous to provide an apparatus and method that provides a single ubiquitous anti-spam module that may be configured to monitor all content incoming to a wireless device prior to being received by any client application. Furthermore, it would be advantageous to provide an apparatus and method operable to analyze the effect of the spam filtering on the wireless device with the goal of blocking further spam attacks.